Peatlands are globally significant carbon reservoirs, yet models for peatland carbon cycling are often limited to the site level. To enable the prediction of carbon dioxide (CO
2
) fluxes in peatlands where no in situ measurements exist, machine learning algorithms must be trained on in situ CO
2
flux measureme...
E. Hettinga, F. Rezanezhad, Ali Reza Shahvaran et al.· Scientific Reports· 0 citations
The Arctic boreal region is rapidly shifting in response to global climate change, including rapid warming and permafrost thaw. Year‐round monitoring of carbon fluxes in these regions is crucial to understanding seasonal and annual carbon budgets, including methane (CH4), a potent greenhouse gas with 80 times the warmi...
M. Montemayor, K. Arndt, Patrick Murphy et al.· Journal of Geophysical Resea...· 0 citations
ABSTRACT Atmospheric methane (CH4) concentrations are accelerating global warming as net emissions increase. Observing systems that quantify sources remain too sparse and fragmented to detect trends—especially in remote regions where climate‐driven natural emissions may be rising. We provide a framework for quantifying...
P. Ciais, S. Peng, J. Chang et al.· Advancement of science· 0 citations
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